Practical considerations for sampling and data analysis in contemporary metagenomics-based environmental studies

Recent advancements in metagenomic-based studies, especially analyses of amplicon-based DNA sequencing targeting taxonomic marker genes, has led to an unprecedented characterization of microbial communities from diverse ecosystems around the world. While originally constrained by a lack of appropriate analytical tools and sequencing depth, new technologies and computational and statistical algorithms have been developed to handle highly dimensional, next-generation sequencing datasets. Both these tools allow for the robust analysis of structural and distributional patterns of microbiota essential for the understanding of microbial ecology and biogeography. Furthermore, consortia of individual laboratories working on large interdisciplinary research programs, like the Human and Earth Microbiome Projects, have developed standardized protocols for DNA extraction, sequencing pipelines, and bioinformatics. These approaches provide large repositories of publicly available data to serve as references for on-going and future, hypothesis-driven studies to better characterize the roles of microbial communities in diverse ecosystems. In this review, we outline the currently available statistical approaches and tools to aid in statistically powered study designs and analyses. Given what is now known about the enormous diversity and variability of the microbial communities in aquatic and terrestrial habitats, we also discuss practical considerations for sample collection. Due to the extensive advances made in the field of metagenomics over the last decade, rigorous, well replicated, hypothesis-driven studies are: 1) needed, 2) now possible, and 3) essential to make best use of sequencing-based technologies to characterize the roles of microbial communities in the structure and function of diverse ecosystems.